MétaCan
Menu
Cohort builder

4,299,418 works, Canadian by any of four routes.

Every filter state is a URL; the URL is the query; the query is citable via /q/⟨hash⟩. The page, the API and the export parse the same parameters.

The current cohort, streamed from the database: every work column, the machine labels, the provisional scores, and the per-row validation status. Exports are capped at 100,000 rows. Mints a permanent /q/ link for this exact query. The same filters always produce the same link, whoever asks.

Search term
Author
Year range
Sort
Language
Type
Field
Venue
BMC Medical Research Methodology
Topic
Retraction
Abstract
Evidence source
Study design
Label agreement
Label status

Direct Codex and Gemma labels are unvalidated and sparse. Distilled predictions cover the full frame and are also unvalidated. Choose the evidence source explicitly; absence of a direct label is never a negative label.

affaffiliation
fundfunder
venuejournal
aboutaboutness

The four routes compose: require the funder route and exclude affiliation to get the funder-only stratum no affiliation-based frame ever sees.

504 results · 1 filter active ·
Results by year
20012025
Publication date
Categories
Machine labels · sparse coverage
Evidence
Language
Type
Citations
An unlabeled work is unknown, not a negative. Label coverage is reported on every query.
504 works in the cohort · of 4,299,418page 2 of 11

Labels cover 25 of 504 works in this cohort. The rest are unlabeled, which is not a negative label: the label table is sparse today and grows as labeling rounds land.

Distilled predictions cover 504 of 504 works in this cohort. Predictions are machine_predicted_unvalidated teacher distillation outputs. Candidate is the union; consensus is the intersection.

afffundgemma · metaresearchgpt · metaresearchmodels split
An optimal search filter for retrieving systematic reviews and meta-analyses
Edwin Lee, Maureen Dobbins, Kara DeCorby, Lyndsey McRae, Daiva Tirilis, Heather Husson
2012· article· en· BMC Medical Research Methodology· Decision Sciences
distilled prediction:candidate · metaresearch+insufficient_payloadconsensus · metaresearch+insufficient_payload
152
citations
affunlabeled
A tutorial on methodological studies: the what, when, how and why
Lawrence Mbuagbaw, Daeria O. Lawson, Livia Puljak, David B. Allison, Lehana Thabane
2020· review· en· BMC Medical Research Methodology· Decision Sciences
distilled prediction:candidate · metaresearch+metaepi_narrow+metaepi_broad+sts+scholarly_communication+open_science+research_integrity+insufficient_payloadconsensus · metaresearch+research_integrity+insufficient_payload
147
citations
fundno affgemma · metaresearch+metaepi_broadgpt · metaresearch+metaepi_broadmodels agree
Quality assessment tools used in systematic reviews of in vitro studies: A systematic review
Linh Tran, Dao Ngoc Hien Tam, Abdelrahman Elshafay, Thao Dang, Kenji Hirayama, Nguyen Tien Huy
2021· review· en· BMC Medical Research Methodology· Decision Sciences
distilled prediction:candidate · metaresearch+metaepi_narrow+metaepi_broad+open_science+research_integrity+insufficient_payloadconsensus · metaresearch+metaepi_narrow+metaepi_broad+research_integrity+insufficient_payload
126
citations
affunlabeled
Development and evaluation of a quality score for abstracts
Antje Timmer, Lloyd R. Sutherland, Robert J. Hilsden
2003· article· en· BMC Medical Research Methodology· Arts and Humanities
distilled prediction:candidate · metaresearch+insufficient_payloadconsensus · metaresearch
119
citations
affunlabeled
Consensus-based recommendations for investigating clinical heterogeneity in systematic reviews
Joel Gagnier, Hal Morgenstern, Doug Altman, Jesse A. Berlin, Stephanie Chang, Peter McCulloch +2 more
2013· review· en· BMC Medical Research Methodology· Decision Sciences
distilled prediction:candidate · metaresearch+metaepi_narrow+metaepi_broad+open_science+research_integrity+insufficient_payloadconsensus · metaresearch+metaepi_broad+research_integrity+insufficient_payload
115
citations
affunlabeled
Machine learning methodologies versus cardiovascular risk scores, in predicting disease risk
Alexandros C. Dimopoulos, Μάρα Νικολαϊδου, Francisco Félix Caballero, Worrawat Engchuan, Albert Sánchez‐Niubò, Holger Arndt +6 more
2018· article· en· BMC Medical Research Methodology· Health Professions
distilled prediction:candidate · metaresearch+metaepi_narrow+sts+research_integrity+insufficient_payloadconsensus · metaresearch+insufficient_payload
113
citations
fundno affgemma · metaresearchgpt · metaresearchmodels split
Evaluating bias due to data linkage error in electronic healthcare records
Katie Harron, Angie Wade, Ruth Gilbert, Berit Müller‐Pebody, Harvey Goldstein
2014· article· en· BMC Medical Research Methodology· Decision Sciences
distilled prediction:candidate · metaresearch+open_science+insufficient_payloadconsensus · metaresearch+insufficient_payload
102
citations
afffundunlabeled
Does group-based trajectory modeling estimate spurious trajectories?
Miceline Mésidor, Marie‐Claude Rousseau, Jennifer O’Loughlin, Marie‐Pierre Sylvestre
2022· article· en· BMC Medical Research Methodology· Computer Science
distilled prediction:candidate · metaresearch+research_integrity+insufficient_payloadconsensus · metaresearch
99
citations
affunlabeled
Which resources should be used to identify RCT/CCTs for systematic reviews: a systematic review
Ellen Crumley, Natasha Wiebe, Kristie Cramer, Terry P. Klassen, Lisa Hartling
2005· review· en· BMC Medical Research Methodology· Decision Sciences
distilled prediction:candidate · metaresearch+metaepi_narrow+metaepi_broad+scholarly_communication+open_science+research_integrity+insufficient_payloadconsensus · metaresearch+metaepi_narrow+metaepi_broad+research_integrity+insufficient_payload
95
citations

How this was built: Screen · Findings · About